1. Field of the Invention
Embodiments of the present invention relate to a recognition technology, and more particularly, to a face image verification method, medium, and apparatus using a kernel based discriminant analysis with local binary pattern (LBP) extraction.
2. Description of the Related Art
Recently, there has been an increased need and/or desire for entrance cards or devices to identify those at airports or attempting to enter buildings or restricted areas, but according to such conventional methods, a key card or key pad given to each person must be used in combination with a card reader to verify the identification information. This results in an inconvenience in that the key card or key pad should always be carried and may even cause a security problem if stolen or lost.
In order to minimize such potential negative aspects, there has been increased interest in biometric technologies that can automatically identify or confirm an individual's identity using biological or behavioral characteristics of the individual. In addition to potentially replacing the need for passwords for a cash withdrawal card or entrance cards for access to buildings or restricted areas, the use of reliable biometric systems has been expanding to include more general applications such as those requiring a high level caution, such as in a safe of a bank, a security system of a company or an airport, and future interfaces between man and machine. For this, many research projects to implement a more convenient and reliable system have been conducted.
Biometric systems and technology use a measurable physical characteristic or personal characteristic in order to verify a personal characteristic or to identify a person. The personal characteristic in the biometric technology may not be stolen, leaked to others, lost, or changed. Accordingly, it may provide advantages enabling a perfect audit function, such as tracking exactly who may infringe a security system.
Among personal characteristics that may be used to implement such a biometric system, there are a person's fingerprints, face, palmprints, particular hand geometries, thermal images, voice characteristics, signatures, vein arrangements, keystroke typing dynamics, retinas, and irises. In particular, it has been found that face recognition is a biometric technology that is most natural and generates relatively the least discomfort since a person's face or appearance is normally most frequently used to identify the person.
However, since conventional face recognition technology identifies people by comparing the characteristics of the contour of a face, there is a potential problem of incorrect recognition that different people may be identified as the same person, and an identical person may be determined to be a different person, e.g., due to the effects of illumination, facial expression, and posture.